Introduction to Structured Query Language

Structured query language (SQL) is a programming language for storing and processing information in a relational database. A relational database stores information in tabular form, with rows and columns representing different data attributes and the various relationships between the data values. Relational database management systems use structured query language (SQL) to store and manage data. The system stores multiple database tables that relate to each other. It is a popular query language that is frequently used in all types of applications. SQL is regularly used not only by database administrators but also by developers writing data integration scripts and data analysts looking to set up and run analytical queries. Data analysts and developers learn and use SQL because it integrates well with different programming languages. For example, they can embed SQL queries with the Java programming language to build high-performing data processing applications with major SQL database systems such as Oracle or MS SQL Server. SQL is also fairly easy to learn as it uses common English keywords in its statements. The term SQL is pronounced ess-kew-ell or sequel.

Before we dive into SQL, let’s demystify some basic terms related to database management systems;

1. Database: A database is a structured set of data. Imagine it as a large container that houses related information. Examples include a customer data table for a business or a bank database system for managing transactions.
2. Table: A table, akin to an Excel spreadsheet, is a specific structure within a database that holds related data. A table consists of rows (records) and columns (fields).
3. Record: A record (or row) in a table represents a single, implicitly structured data item, like a customer’s details or a single transaction in a bank.
4. Field: A field (or column) in a table holds a specific piece of information, like a customer’s name or transaction amount.
5. Primary Key: A primary key is a unique identifier for a record in a table. It ensures that each record within a table can be distinctly identified.

SQL is used for the following:

1. Modifying database table and index structures.
2. Adding, updating and deleting rows of data.
3. Retrieving subsets of information from within relational database management systems (RDBMSes). This information can be used for transaction processing, analytics applications and other applications that require communicating with a relational database.

SQL queries and other operations take the form of commands written as statements and are aggregated into programs that enable users to add, modify or retrieve data from database tables. A table is the most basic unit of a database and consists of rows and columns of data. A single table holds records, and each record is stored in a row of the table. Tables are the most used type of database objects or structures that hold or reference data in a relational database. Other types of database objects include the following:

• Views are logical representations of data assembled from one or more database tables.
• Indexes are lookup tables that help speed up database lookup functions.
• Reports consist of data retrieved from one or more tables, usually a subset of that data that is selected based on search criteria.

Each column in a table corresponds to a category of data -- for example, customer name or address -- while each row contains a data value for the intersecting column.

SQL implementation involves a server machine that processes the database queries and returns the results. The SQL process goes through several software components, including the following:

• Parser
  The parser starts by tokenizing, or replacing, some of the words in the SQL statement with special symbols. It then checks the statement for the following;
  Correctness
  The parser verifies that the SQL statement conforms to SQL semantics, or rules, that ensure the correctness of the query statement. For example, the parser checks if the SQL command ends with a semi-colon. If the semi-colon is missing, the parser returns an error.
  Authorization
  The parser also validates that the user running the query has the necessary authorization to manipulate the respective data. For example, only admin users might have the right to delete data.

• Relational engine
  The relational engine, or query processor, creates a plan for retrieving, writing, or updating the corresponding data in the most effective manner. It checks for similar queries, reuses previous data manipulation methods, or creates a new one. It writes the plan in an intermediate-level representation of the SQL statement called byte code. Relational databases use byte code to efficiently perform database searches and modifications.

• Storage engine
  The storage engine, or database engine, is the software component that processes the byte code and runs the intended SQL statement. It reads and stores the data in the database files on physical disk storage. Upon completion, the storage engine returns the result to the requesting application.

SQL commands
Structured query language (SQL) commands are specific keywords or SQL statements that developers use to manipulate the data stored in a relational database. You can categorize SQL commands as follows;
Data definition language (DDL) - refers to SQL commands that design the database structure. Database engineers use DDL to create and modify database objects based on the business requirements. For example, the database engineer uses the CREATE command to create database objects such as tables, views, and indexes.
Data query language (DQL) - consists of instructions for retrieving data stored in relational databases. Software applications use the SELECT command to filter and return specific results from a SQL table.
Data manipulation language (DML) - DML statements write new information or modify existing records in a relational database. For example, an application uses the INSERT command to store a new record in the database.
Data control language - Database administrators use data control language (DCL) to manage or authorize database access for other users. For example, they can use the GRANT command to permit certain applications to manipulate one or more tables.
Transaction control language - The relational engine uses transaction control language (TCL) to automatically make database changes. For example, the database uses the ROLLBACK command to undo an erroneous transaction.

SQL is a great language to learn because it's the primary database language used for data processing tasks and is used across various industries. The following reasons highlight the importance of SQL;

• Backbone of the data industry. SQL is considered the backbone of the data industry. It's widely used by data-centric professionals including data analysts, data scientists, business analysts and database developers.

• Universal language. SQL is a universal language that is transferable to other disciplines and languages. Learning SQL can help one understand the workings of other languages such as Python and Java. It also makes collaboration easy, as it has a large supportive community.

• In-demand skill. SQL knowledge is one of the most in-demand skills in the field of data science. It appears in a significant percentage of data science job postings, making it a prized skill for professionals in this field.

• Data manipulation. SQL is well-suited for data manipulation. It enables users to easily test and manipulate data, making it efficient for tasks such as filtering, sorting and aggregating data.

• Rapid query processing. SQL enables rapid query processing, enabling users to retrieve, manipulate or store data quickly and efficiently. However, optimizing queries for rapid processing involves a combination of proper indexing, query optimization and database design considerations.

• Security features. SQL provides various security features such as authentication, access control, audit trails and encryption, making it easy to manage permissions and ensure the security of data.

• Commonality and compatibility. SQL is widely used in various IT systems and is compatible with multiple other languages. Its commonality benefits beginners in the profession, as they are likely to use SQL throughout their careers. It also contributes to ease of application and improves the production and efficiency of businesses.

• Scalability. SQL is suitable for organizations of any size. It can easily scale up to accommodate future growth, making it a versatile choice for small and large businesses alike.

• Open source and community support. SQL is an open source language with a vibrant community of developers that regularly provide updates and troubleshooting assistance to SQL users.

• Cost-effective. Due to its open source nature, SQL is more cost-effective than proprietary solutions, making it ideal for organizations with budget constraints.

Commonly used SQL commands
Most SQL commands are used with operators to modify or reduce the scope of data operated on by the statement. Some commonly used SQL commands are;
SQL SELECT. The SELECT command is used to get some or all data in a table. SELECT can be used with operators to narrow down the amount of data selected.
SQL CREATE. The CREATE command is used to create a new SQL database or SQL table. Most versions of SQL create a new database by creating a new directory, in which tables and other database objects are stored as files.
The CREATE DATABASE statement creates a new SQL database while the CREATE TABLE command is used to create a table in SQL.
SQL DELETE. The DELETE command removes rows from a named table.
SQL INSERT INTO. The INSERT INTO command is used to add records into a database table.
SQL UPDATE. The UPDATE command is used to make changes to rows or records in a specific table.
SQL statements can use loops, variables and other components of a programming language to update records based on different criteria.

To ensure optimal performance and ease of use, follow these SQL best practices;

1. Naming Conventions: Use clear, concise names for tables and columns. The names should describe the data they hold.
2. Data Types: Be specific about your data types. If a numeric column will only hold integers, specify it as such.
3. Indexing: Use indexing wisely to speed up data retrieval. However, remember that while indexes speed up data retrieval, they can slow down data input.
4. Backing up Data: Always backup your data regularly to prevent data loss in case of any failure or corruption.

SQL’s relational engine and storage engine work hand in hand to ensure efficient data management and retrieval. These elements, combined with SQL’s versatility across operating systems and database software, make SQL a crucial skill for aspiring database administrators and software engineers alike.

SQL, or Structured Query Language, is a standard language for managing and manipulating relational databases. Understanding SQL basics and syntax, mastering database management with SQL, and adhering to SQL best practices are foundational skills for anyone dealing with data.